Zhang, Yinping and Chuah, Joon Huang and Khairuddin, Anis Salwa Mohd and Chen, Dongyang and Li, Jingjing and Xia, Chenyang (2024) An Intelligent Guava Grading System Based on Machine Vision. Journal of Food Process Engineering, 47 (11). e14753. ISSN 0145-8876, DOI https://doi.org/10.1111/jfpe.14753.
Full text not available from this repository.Abstract
Ensuring efficient grading of guavas is crucial for timely postharvest storage and maximizing profits. Currently, the subjective nature of manual grading underscores the need for more sophisticated methodologies. However, employing machine vision for intelligent grading faces hurdles due to the diverse characteristics of guavas and the high development costs. This research targets the limitations in the guava grading process and introduces an intelligent system to overcome them. The system's structure and operational procedures were outlined, establishing diverse standards encompassing guava color, shape, size, and integrity. Image capture and preprocessing of guavas are completed. Employing the RGB model, the study performed color feature extraction and guava recognition, alongside diameter and integrity assessment through edge detection. Following a thorough analysis of various models, ResNet50 emerged as the preferred choice for guava image evaluation and depth recognition. Subsequently, an intelligent guava grading system was developed using Microsoft Visual Studio 2017. Experimental results demonstrated outstanding grading accuracy of 98.05%, with grading speed averaging 5.47 times faster than manual methods. Compared to traditional manual grading techniques, the system excelled in work efficiency, speed, reliability, and robustness.
| Item Type: | Article |
|---|---|
| Funders: | Chuzhou University (IMG001-2022) ; (202310377042), Universiti Malaya, Malaysia |
| Uncontrolled Keywords: | convolutional neural networks; guava; image recognition; intelligent grading; machine vision |
| Subjects: | S Agriculture > S Agriculture (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering > Department of Electrical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 17 Feb 2025 06:51 |
| Last Modified: | 17 Feb 2025 06:51 |
| URI: | http://eprints.um.edu.my/id/eprint/47382 |
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